If your image is just a grayscale image, that you can represent it in one matrix with a variety of entries, you can convert it to a matrix and manipulate these entries.

On the other hand, if you have an RGB-scale image, then you have to be careful when you say "omit some parts" because you need to "REPLACE" them with something that can make up the omitted part in the image. Otherwise, you will get like a hole in the image... (This technique is called inpainting images)

See these links for more details

https://www.mathworks.com/matlabcentral/answers/144108-how-to-remove-specific-portions-of-a-image

https://www.mathworks.com/matlabcentral/answers/154845-how-to-delete-selective-part-of-image

Hi,

You can use this example:

https://www.youtube.com/watch?v=RaOr4A50i4M&ab_channel=Maggie

The problem is very simple and straightforward, you just need to convert the image into binary then make MATLAB identify the regions in the image. After identifying the regions you can easily remove the dot by making it equals [1].

If your image is just a grayscale image, that you can represent it in one matrix with a variety of entries, you can convert it to a matrix and manipulate these entries.

On the other hand, if you have an RGB-scale image, then you have to be careful when you say "omit some parts" because you need to "REPLACE" them with something that can make up the omitted part in the image. Otherwise, you will get like a hole in the image... (This technique is called inpainting images)

See these links for more details

https://www.mathworks.com/matlabcentral/answers/144108-how-to-remove-specific-portions-of-a-image

https://www.mathworks.com/matlabcentral/answers/154845-how-to-delete-selective-part-of-image

Hi Nasim, use this MATLAB code.

% Read the image

img = imread('yourImage.png');

% Binarize the image

BW = imbinarize(img);

% Label connected components in the image and generate the mask

L = bwlabel(BW);

mask = (L == 2);

% Dilate the binary mask a bit to include more pixels

mask = imdilate(mask, strel('diamond', 3));

% Set values = 0 where mask = 1

newImg = img;

newImg(mask) = 0;

% Visualize

imagesc([img, newImg])

axis image off

Subhadeep Koley Thank you very much it was really useful.